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» Outliers and Bayesian Inference
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CVPR
2010
IEEE
13 years 8 months ago
Robust RVM regression using sparse outlier model
Kernel regression techniques such as Relevance Vector Machine (RVM) regression, Support Vector Regression and Gaussian processes are widely used for solving many computer vision p...
Kaushik Mitra, Ashok Veeraraghavan, Rama Chellappa
ISMIS
2005
Springer
14 years 2 months ago
Robust Inference of Bayesian Networks Using Speciated Evolution and Ensemble
Recently, there are many researchers to design Bayesian network structures using evolutionary algorithms but most of them use the only one fittest solution in the last generation. ...
Kyung-Joong Kim, Ji-Oh Yoo, Sung-Bae Cho
IJAR
2006
125views more  IJAR 2006»
13 years 8 months ago
Compiling relational Bayesian networks for exact inference
We describe in this paper a system for exact inference with relational Bayesian networks as defined in the publicly available Primula tool. The system is based on compiling propos...
Mark Chavira, Adnan Darwiche, Manfred Jaeger
ICML
2007
IEEE
14 years 9 months ago
Robust multi-task learning with t-processes
Most current multi-task learning frameworks ignore the robustness issue, which means that the presence of "outlier" tasks may greatly reduce overall system performance. ...
Shipeng Yu, Volker Tresp, Kai Yu
RSFDGRC
2005
Springer
208views Data Mining» more  RSFDGRC 2005»
14 years 2 months ago
On the Complexity of Probabilistic Inference in Singly Connected Bayesian Networks
Abstract. In this paper, we revisit the consensus of computational complexity on exact inference in Bayesian networks. We point out that even in singly connected Bayesian networks,...
Dan Wu, Cory J. Butz